diff --git a/.github/workflows/auto_publish.yml b/.github/workflows/auto_publish.yml index 70cc96b..465447f 100644 --- a/.github/workflows/auto_publish.yml +++ b/.github/workflows/auto_publish.yml @@ -21,7 +21,7 @@ on: type: boolean default: false push: - branches: [main] + branches: [main-old] jobs: diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 8f79c6c..f300c28 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -2,9 +2,9 @@ name: Run tests on: push: - branches-ignore: [ main ] + branches-ignore: [ main-old ] pull_request: - branches-ignore: [ main ] + branches-ignore: [ main-old ] workflow_call: workflow_dispatch: @@ -14,7 +14,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: ["3.8", "3.9", "3.10"] + python-version: ["3.9", "3.10"] poetry-version: ["1.8"] runs-on: ubuntu-latest diff --git a/.vscode/settings.json b/.vscode/settings.json index 6d41b75..31f5f6e 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -1,12 +1,10 @@ { - "python.linting.pylintEnabled": true, "python.defaultInterpreterPath": "/usr/local/bin/python", "python.terminal.activateEnvironment": false, - "python.formatting.provider": "black", - "python.analysis.typeCheckingMode": "strict", + "python.analysis.typeCheckingMode": "basic", "editor.formatOnSave": true, "editor.codeActionsOnSave": { - "source.organizeImports": true + "source.organizeImports": "explicit" }, "git.pullTags": false, "ltex.language": "en-GB", diff --git a/README.md b/README.md index 0b588cd..81c3822 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,12 @@ # mini-transcript-search -Experiment in low dependency vector search \ No newline at end of file +This is an experiment in low dependency vector search. + +For just checking a few days - we don't need an index or a big database. We can just calculate cosine similarity directly. + +See infer.ipynb for usage as a module. + +```bash +python -m mini_transcript_search "register of members financial interests" --threshold 0.4 --n 5 +``` + diff --git a/notebooks/infer.ipynb b/notebooks/infer.ipynb new file mode 100644 index 0000000..06856cc --- /dev/null +++ b/notebooks/infer.ipynb @@ -0,0 +1,45 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from mini_transcript_search import ModelHandler\n", + "import datetime\n", + "from pathlib import Path\n", + "\n", + "handler = ModelHandler(use_local_model=False, override_stored=True)\n", + "\n", + "search_query = \"register of members financial interests\"\n", + "\n", + "yesterday = datetime.date.today() - datetime.timedelta(days=1)\n", + "\n", + "# the last week starting yesterday\n", + "last_week = ModelHandler.DateRange(start_date=yesterday, end_date=yesterday)\n", + "results = handler.query(\n", + " search_query,\n", + " threshold=0.4,\n", + " n=10,\n", + " date_range=last_week,\n", + " chamber=ModelHandler.Chamber.COMMONS,\n", + " transcript_type=ModelHandler.TranscriptType.DEBATES,\n", + ")\n", + "\n", + "# dump csv\n", + "results.df().to_csv(Path(\"last_week.csv\"), index=False)\n", + "\n", + "# dump json\n", + "results.to_path(Path(\"last_week.json\"))" + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/poetry.lock b/poetry.lock new file mode 100644 index 0000000..d11fffe --- /dev/null +++ b/poetry.lock @@ -0,0 +1,2119 @@ +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. + +[[package]] +name = "annotated-types" +version = "0.7.0" +description = "Reusable constraint types to use with typing.Annotated" +optional = false +python-versions = ">=3.8" +files = [ + {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, + {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, +] + +[[package]] +name = "anyio" +version = "4.4.0" +description = "High level compatibility layer for multiple asynchronous event loop implementations" +optional = false +python-versions = ">=3.8" +files = [ + {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"}, + {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"}, +] + +[package.dependencies] +exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} +idna = ">=2.8" +sniffio = ">=1.1" +typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} + +[package.extras] +doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] +test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] +trio = ["trio (>=0.23)"] + +[[package]] +name = "astroid" +version = "2.15.8" +description = "An abstract syntax tree for Python with inference support." +optional = false +python-versions = ">=3.7.2" +files = [ + {file = "astroid-2.15.8-py3-none-any.whl", hash = "sha256:1aa149fc5c6589e3d0ece885b4491acd80af4f087baafa3fb5203b113e68cd3c"}, + {file = "astroid-2.15.8.tar.gz", hash = "sha256:6c107453dffee9055899705de3c9ead36e74119cee151e5a9aaf7f0b0e020a6a"}, +] + +[package.dependencies] +lazy-object-proxy = ">=1.4.0" +typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} +wrapt = [ + {version = ">=1.11,<2", markers = "python_version < \"3.11\""}, + {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}, +] + +[[package]] +name = "certifi" +version = "2024.8.30" +description = "Python package for providing Mozilla's CA Bundle." +optional = false +python-versions = ">=3.6" +files = [ + {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"}, + {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"}, +] + +[[package]] +name = "charset-normalizer" +version = "3.3.2" +description = "The Real First Universal Charset Detector. 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5d8e81e..3b6f4f8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,16 +13,25 @@ include = [ [tool.poetry_bumpversion.file."src/mini_transcript_search/__init__.py"] +[tool.poetry.scripts] +transcript-search = "mini_transcript_search.__main__:app" + [tool.poetry.dependencies] -python = "^3.8" +python = "^3.9,<3.13" +mysoc-validator = "^0.3.0" +fastembed = "^0.3.6" +numpy = "1.26.4" +pandas = "^2.2.2" +requests = "^2.32.3" +pyarrow = "^17.0.0" [tool.poetry.group.dev.dependencies] pytest = "^7.1.2" pytest-cov = "^3.0.0" pylint = "^2.12.2" -ruff = "^0.4.4" pyright = "^1.1" toml = "^0.10.2" +ruff = "^0.6.4" [build-system] requires = ["poetry-core>=1.0.0"] diff --git a/src/mini_transcript_search/__init__.py b/src/mini_transcript_search/__init__.py index d540f47..2c3ecfa 100644 --- a/src/mini_transcript_search/__init__.py +++ b/src/mini_transcript_search/__init__.py @@ -1,4 +1,9 @@ """ Experiment in low dependency vector search """ -__version__ = "0.1.0" \ No newline at end of file + +from .search import ModelHandler + +__version__ = "0.1.0" + +__all__ = ["ModelHandler", "__version__"] diff --git a/src/mini_transcript_search/__main__.py b/src/mini_transcript_search/__main__.py new file mode 100644 index 0000000..12ff698 --- /dev/null +++ b/src/mini_transcript_search/__main__.py @@ -0,0 +1,64 @@ +import datetime +from typing import Annotated, Optional, Union + +import typer +from mysoc_validator.models.consts import Chamber, TranscriptType + +from .search import ModelHandler, default_model + +app = typer.Typer() +yesterday = datetime.date.today() - datetime.timedelta(days=1) + +handler = ModelHandler(use_local_model=False) + +yesterday = datetime.date.today() - datetime.timedelta(days=1) +last_week = yesterday - datetime.timedelta(days=7) + + +def parse_date(date: Union[datetime.date, str]) -> datetime.date: + if isinstance(date, datetime.date): + return date + return datetime.date.fromisoformat(date) + + +DateField = Annotated[datetime.date, typer.Argument(parser=parse_date)] + + +@app.command() +def search( + query: str, + threshold: float = 0.2, + n: Optional[int] = None, + start_date: DateField = yesterday, + end_date: DateField = yesterday, + chamber: Chamber = Chamber.COMMONS, + transcript_type: TranscriptType = TranscriptType.DEBATES, + model_id: str = default_model, + use_local_model: bool = True, + override_stored: bool = False, +): + handler = ModelHandler( + model_id=model_id, + use_local_model=use_local_model, + override_stored=override_stored, + ) + + # if threshold is a float greater than one, convert to int + if threshold > 1: + threshold = int(threshold) + + date_range = ModelHandler.DateRange(start_date=start_date, end_date=end_date) + results = handler.query( + query=query, + threshold=threshold, + n=n, + date_range=date_range, + chamber=chamber, + transcript_type=transcript_type, + ) + + typer.echo(results.json()) + + +if __name__ == "__main__": + app() diff --git a/src/mini_transcript_search/inference.py b/src/mini_transcript_search/inference.py new file mode 100644 index 0000000..b8bcd0f --- /dev/null +++ b/src/mini_transcript_search/inference.py @@ -0,0 +1,67 @@ +import os +from contextlib import redirect_stderr +from typing import Optional + +import numpy as np +import pandas as pd +import requests +from fastembed import TextEmbedding # type: ignore +from numpy.typing import NDArray + + +class Inference: + """ + Class to handle inference for text embeddings. + Uses hugging faces free api if not local, but setting local + will use fastembed's approach + """ + + def __init__( + self, model_id: str, hf_token: Optional[str] = None, local: bool = False + ): + self.model_id: str = model_id + self.hf_token = hf_token if hf_token else os.environ.get("HF_TOKEN", None) + self.local = local + self._model = None + if self.hf_token is None and self.local is False: + raise ValueError("Need to set hf_token for remote embedding generation.") + + def query_local(self, texts: list[str]) -> list[NDArray[np.float64]]: + if self._model is None: + # suppress download progerss bar + with open(os.devnull, "w") as fnull: + with redirect_stderr(fnull): + self._model = TextEmbedding(model_name=self.model_id) + return list(self._model.embed(texts)) # type: ignore + + def query_remote(self, texts: list[str]) -> list[NDArray[np.float64]]: + api_url = f"https://api-inference.huggingface.co/pipeline/feature-extraction/{self.model_id}" + headers = {"Authorization": f"Bearer {self.hf_token}"} + response = requests.post( + api_url, + headers=headers, + json={"inputs": texts, "options": {"wait_for_model": True}}, + ) + return response.json() + + def query_id_and_text(self, id_and_text: dict[str, str]) -> pd.DataFrame: + id_values = list(id_and_text.keys()) + text_values = list(id_and_text.values()) + embeddings = self.query(text_values) + if isinstance(embeddings, dict): + raise ValueError(f"Error in embeddings: {embeddings}") + return pd.DataFrame( + { + "id": id_values, + "text": text_values, + "embedding": embeddings, + } + ) + + def query(self, texts: list[str]): + if len(texts) == 0: + return [] + if self.local: + return self.query_local(texts) + else: + return self.query_remote(texts)